OpenAI’s Sam Altman: AI great for those early in their careers

One of my favorite podcasts is Hard Fork, a weekly technology show co-hosted by New York Times columnist Kevin Roose and veteran tech reporter for The New York Times and Casey Newton of Platformer. Their goal is straightforward: explore the stories unfolding at “the wild frontier of tech,” separating hype from reality. Imagine two sharp, well-informed journalists dissecting the future that’s already here. They interview industry leaders, unpacking breakthroughs, and pushing back on the narratives shaping our digital world. It’s part of the NYT’s audio lineup and drops new episodes every week.

This past week, Hard Fork hosted its first live recording in front of an audience. About 700 people gathered at Hard Fork Live in San Francisco to hear conversations with a number of guests, two of whom were OpenAI’s CEO Sam Altman and COO Brad Lightcap. While the discussion spanned everything from generative models to governance, one section stood out to me: their deep dive into how artificial intelligence is reshaping employment, especially for early-career professionals.

Sam Altman offered a perspective that sharply contrasts with the prevailing narrative that AI will decimate white-collar entry-level jobs. Instead, he argued that AI is likely to benefit those just entering the workforce. He likened AI tools to supercharged co-pilots, helping early-career employees perform work they’d normally take months or years to master. By automating repetitive tasks and offering intelligent suggestions, AI allows younger workers to contribute meaningfully almost from day one. Altman’s view is that rather than replacing early-career talent, AI can shorten their ramp-up period and accelerate their development. It’s not about automation stealing jobs. It’s about augmentation, creating faster paths to value.

Brad Lightcap reinforced that point with a more operational lens. He acknowledged that OpenAI regularly works with businesses across sectors, and those companies are not reporting mass elimination of junior roles. If anything, Lightcap said the most profound impact AI is having is among people early in their careers. These are the employees who typically lack the depth of experience that enables quick problem-solving or the confidence to contribute at scale. AI fills that gap. It helps them write better, code faster, and analyze more deeply. When paired with the right leadership and structure, AI isn’t pushing juniors out, it’s pulling them up.

Of course, the hosts pushed back, as they should have. Kevin Roose asked whether there’s a risk of new workers becoming overly reliant on AI, letting the machine do all the thinking. Casey Newton questioned whether that would stunt their growth, leaving them without the critical judgment and creativity that professional maturity requires. Both Altman and Lightcap agreed that those risks are real, but avoidable. The key is not to drop AI tools into workplaces and walk away. It’s to pair them with real mentorship and ongoing learning. Juniors still need human support: guidance from managers, feedback from peers, and a safe space to fail and learn. AI can’t replace those essentials, but it can enhance them.

They also acknowledged the need for structural changes. Organizations that truly want to leverage AI to support early-career talent must think deliberately about how they onboard, train, and mentor. Altman noted that OpenAI’s own internal practices reflect this belief. New hires, especially those earlier in their careers, are encouraged to use AI tools, but also expected to engage in thoughtful discussions about their outputs. This two-pronged approach ensures they’re learning not just how to use AI, but also how to critique it, question it, and improve upon what it suggests.

Notably, both Altman and Lightcap rejected the more dire predictions circulating within the tech community. One such prediction, from Anthropic CEO Dario Amodei, suggested that AI could eliminate up to half of all entry-level white-collar jobs within five years. Altman and Lightcap disagreed. They pointed out that there’s little evidence to support such claims, and even if the technology progresses quickly, adoption will not. Most companies are slow to change. Many still struggle to modernize their onboarding processes, let alone fully implement AI workflows. Any workforce disruption will be slower and more nuanced than the headlines suggest.

What resonated most for me was how they framed AI not as a replacement for early-career talent, but as a force multiplier. When used thoughtfully, AI has the potential to accelerate careers, not cut them short. It can help interns produce stronger work. It can allow new grads to test ideas and iterate faster. And it can give junior employees a seat at the table earlier than they would’ve otherwise earned. But the key isn’t the tool—it’s the system around it. Employers must treat AI as a catalyst, not a crutch. That means embedding it into learning programs, encouraging human oversight, and rewarding judgment and creativity over button-pushing.

The conversation was a reminder that we have choices. Technology doesn’t dictate outcomes—how we choose to use it does. AI can be the reason fewer entry-level jobs exist. Or it can be the reason those jobs are more valuable, more dynamic, and more rewarding than ever before. If we make the right choices, we may find that AI is not the threat we fear—it’s the opportunity we’ve been waiting for.